Brain-wide human oscillatory local field potential activity during visual working memory

Summary Oscillatory activity in the local field potential (LFP) is thought to be a marker of cognitive processes. To understand how it differentiates tasks and brain areas in humans, we recorded LFPs in 15 adults with intracranial depth electrodes, as they performed visual-spatial and shape working memory tasks. Stimulus appearance produced widespread, broad-band activation, including in occipital, parietal, temporal, insular, and prefrontal cortex, and the amygdala and hippocampus. Occipital cortex was characterized by most elevated power in the high-gamma (100–150 Hz) range during the visual stimulus presentation. The most consistent feature of the delay period was a systematic pattern of modulation in the beta frequency (16–40 Hz), which included a decrease in power of variable timing across areas, and rebound during the delay period. These results reveal the widespread nature of oscillatory activity across a broad brain network and region-specific signatures of oscillatory processes associated with visual working memory.


INTRODUCTION
Working memory, the ability to hold and manipulate information in the mind for a short period of time, is central for many cognitive processes, including planning, problem-solving, and decision-making. 1,24][5] For this reason, understanding the neural basis of working memory has been a long-standing question in cognitive neuroscience research. 6Neurophysiological experiments in non-human primates have identified neuronal activation of the prefrontal cortex as central for the maintenance of working memory. 7Persistent activity generated by the spiking of prefrontal neurons is also associated with distinct patterns of spectral power, identifiable in local field potential recordings. 8,9owever, other lines of evidence, and particularly human functional imaging studies, suggest a much more widespread pattern of activation during working memory. 10Imaging studies have been successful in using multi-variate methods to decode the remembered visual stimuli from visual cortical area voxels. 11Although some neurophysiological studies have failed to detect persistent activity in the sensory cortices, 12 it has been argued on theoretical grounds that no overall elevation of activity is necessary for cortical neurons to encode information, an idea often referred to as ''activity-silent'' mechanisms of working memory. 13Cellular and synaptic mechanisms have been implicated in the maintenance of working memory. 14,15Correspondingly, whether the contents of working memory are maintained in the prefrontal or in the sensory cortex has been a matter of debate. 16,17art of the problem in reconciling these contrasting viewpoints is the use of different methodologies across human and animal studies. 181][22][23] Analysis of non-human primate recordings has also begun to mirror methods of analysis inspired by human studies. 24However, differences in behavioral paradigms and methods of analyses persist and make comparison of findings from different models challenging.We were therefore motivated to collect and analyze local field potentials (LFPs) obtained from intracranial recordings in human subjects, using working memory behavioral paradigms and analysis methods that parallel those used in animal models.Our results provide a direct way to compare and reconcile findings in the respective research literatures of the two fields.electrodes were available in the 6s-delay spatial task (172, 79, 355, 37, 109, and 253 contacts in the six regions, respectively).Similarly, 854 contacts from 153 electrodes were available in the shape task (136, 46, 322, 37, 103, and 210 contacts in the six regions, respectively).Spectral power was computed in each trial and contact and then averaged within each region, for plotting purposes; we treated each electrode contact as one observation for statistical analysis.

Signatures of spectral power for visual stimuli
Our analysis first focused on how the visual stimuli themselves induced LFP power across spectral bands and areas.We therefore determined the time course of induced LFP power during the trial.Mean power in six different brain regions is shown for the two versions (3-s and 6-s delay) of the spatial working memory task in Figures 2 and S1, respectively.The most salient finding of this analysis was a broadband signal during the appearance of the stimulus.This was present not only in the visual areas of the occipital lobe but also in the temporal, parietal, and prefrontal association cortices and even in areas not traditionally linked to strong sensory responses, such as the cingulate and mesial temporal lobe (see cue presentation interval between the dotted lines at 1 and 1.5 s in Figure 2).The broadband power elevation remained prominent when plotting the power spectrum in a logarithmic frequency scale (Figure S2).The effect of stimulus presentation diminished for the shape working memory task (Figure 3), which involved presentation of stimuli over the fovea, replacing the pre-existing fixation point.Only in this latter task, the presentation of the visual stimulus elicited preferential broadband activation in the occipital cortex, although an LFP power transient was also evident in parietal and prefrontal cortex (Figure 3).
The most differentiating effect of the cue appearance across regions was the extent of the increase in high-gamma (100-150 Hz) power, which is likely most closely tied to neuronal spiking. 20To identify differences between regions and conditions, we calculated power in each task epoch, after subtracting at each frequency the baseline power, which was computed in the inter-trial interval.We averaged this power for all trials obtained from each contact in a given electrode and treated it as a single observation (though treating multiple electrode contacts from the same patient, as distinct).We adopted a mixed-effects model, with brain regions as a fixed factor and added Behavioral tasks and recording methods (A) Spatial manual delayed response task.At the start of each trial, a circle appears in the center of the tablet screen, and the subject moves the stylus into the circle to initiate the trial.After 1 s, a second white dot appears (Cue) at a peripheral location for 0.5 s, after which only the center circle remains.After a delay period, the center circle disappears, and the subject needs to drag the stylus across the screen into the remembered location of the cue.(B) Shape delayed match-nonmatch task.At the start of each trial, a white circle appears in the center of the tablet screen, and the subject moves the stylus into the circle to initiate the trial.After a delay period, a white polygon replaces the center circle for 0.5 s (Cue), followed by the reappearance of the center circle.After a delay, a second convex polygon replaces the center circle for 0.5 s, followed by the reappearance of the center circle.After a second delay, the center circle disappears, and the subject needs to drag the stylus to either a green or red peripheral circle to indicate whether the two polygons were the same or not.(C) Example MRI scan of one patient, with electrode position, based on CT scan, superimposed, where LFP recording were made.a random effect term for the participants, to avoid the confound of unequally represented electrode contacts in regions across participants.Averaging power in this range across the entire cue presentation period revealed a highly significant difference between the six regions in the 3-s spatial working memory task (F 5,1096 = 19.98,p = 2.2E-16, effect size: h 2 = 0.09).The occipital region exhibited the highest power in the high-gamma range compared with all other regions (Tukey post-hoc test, evaluated at the a = 0.05 significance level).High-gamma power was also significantly different between areas in the 6-s delay version of the spatial task (F 5,998 = 19.06,p = 2.2E-16, effect size: h 2 = 0.09) and in the shape working memory task (F 5,840 = 2.78, p = 0.02, effect size: h 2 = 0.02).The occipital region again exhibited significantly higher power in high-gamma frequency compared with all other regions (Tukey post-hoc test, evaluated at the a = 0.05 significance level).

Delay-period LFP power
We next tested whether the high-gamma power differences observed in the cue presentation interval carried over to the delay period.This was generally not the case.High-gamma power in the occipital cortex essentially returned to the pre-fixation baseline during the delay interval (Figure 4B).Instead, substantial differences during the delay interval were mostly evident in the high-beta frequency band (16-40 Hz).Shortly after the cue appearance, beta power decreased with a timing of the beta frequency trough that differed between areas.In the 3-s delay spatial task, it reached a minimum at the occipital cortex after the stimulus offset, at the parietal cortex 150 ms later, and the prefrontal cortex another 650 ms later (Figure 2).A trough was also evident in the 6-s spatial task (Figure 4A).Averaging between power across the delay period revealed systematic differences between regions in the 3-s and 6-s spatial task (Figure S3, F 5,1006 = 3.24, p = 0.007, effect size: h 2 = 0.02 and F 5,995 = 11.37,p = 1.1E-10, effect size: h 2 = 0.05 for the two versions, respectively).In the shape task, a beta power trough was evident around each of the two stimulus presentations (Figure 4C), which rebounded earlier the baseline during the delay interval, particularly for the occipital and prefrontal cortex.In this case, too, beta power differed systematically between regions during the first delay period (F 5,840 = 12.03, p = 2.88E-11, effect size: h 2 = 0.07), with the occipital region exhibiting the greatest amplitude (Figure 4C).The prefrontal cortex was the area with the highest power throughout the delay period of the task (Figure 4D).

Task differences
The two versions of the spatial task imposed different difficulty in terms of their working memory requirement (3 vs. 6 s of working memory maintenance period).This was also reflected in the performance of subjects in the two versions of the tasks, which was lower in the 6-s delay variant: 79% vs. 69% for Task 1 and Task 2, respectively, in Table 1, a significant difference (two-tailed paired t test, t 14 = 4.93, p = 0.0004).This difference resulted in differences in spectral power across regions, specifically in the high-gamma range (Figure 5).Here, we adopted a mixedeffects model, with fixed factors, the regions, and the 3-s/6-s version of the spatial task and added a random effect term for participants.We considered the first 3 s of the delay period in the two task versions to compare power.High-gamma power was higher in the 6-s delay version of the task (F 1,2004 = 54.86,p = 1.89E-13, effect size: h 2 = 0.03 for main effect of task).We also found an interaction between regions and versions of the spatial task (F 5,2004 = 4.32, p = 0.0006, effect size: h 2 = 0.01).The parietal region (Figure 5) exhibited significantly higher power compared with other regions (F 5,2007 = 4.21, p = 0.0008, effect size: h 2 = 0.01, Tukey post-hoc test, evaluated at the a = 0.05 significance level).It was also notable that the elevated high-gamma power in the 6-s version of the task was already present in the fixation period, prior to the appearance of the stimulus or the delay period.Because the tasks were presented in blocks, the result suggests that the participants' level of effort or expectations about the task modulated systematically spectral power.Such differences were mostly absent in the beta frequency range (Figure S3).We also considered high-gamma power in the delay period recorded from the same electrode contacts that were available in both 3-s and 6-s version of the spatial task (Figure S4).Because contacts were perfectly balanced across subjects in this analysis, we relied on a repeated measures ANOVA model.This analysis revealed that delay-period high-gamma power differed systematically between the two tasks (F 1,989 = 9.72, p = 3.4E-11) with power in the parietal and occipital areas exhibiting the greatest difference between tasks.
The shape task differed in the type of stimuli that needed to be maintained in memory (shapes rather than spatial locations), the part of the visual field where the stimuli appeared (central vs. peripheral), and also in the nature of the task (requiring a judgment on whether the second stimulus was match or nonmatch and preparation of a motor response based on a color rule).As already mentioned, the broadband increase in power that was observed across all areas when peripheral visual stimuli were presented in the spatial working memory task was more limited to the occipital cortex in this case (Figure S1).To perform the shape task, it was still essential for subjects to maintain the identity of the stimulus in memory at least during the first delay period.Thus, we examined how the high-gamma differed between regions as the subjects were engaged in this function (Figures 3 and 4).High-gamma power differed even less so between regions in the shape task (Figure 4D, F 5,840 = 1.11, p = 0.35) than in the spatial task.
We next compared high-gamma power between the spatial and shape task.Here, we adopted a mixed-effects model, with fixed factors, the regions and tasks, and added a random effect term for participants.We first considered the average power of the first 3 s in the delay period of the 6-s version of the spatial task and the first delay period of the shape task.High-gamma power was higher overall in the spatial task (F 1,1837 = 91.3,p = 2E-16, effect size: h 2 = 0.05 for main effect of task).This analysis revealed no main effect of differences between regions (F 5,1837 = 0.65, p = 0.66, effect size: h 2 = 0.001).An interaction between regions and tasks (F 5,1834 = 2.84, p = 0.01, effect size: h 2 = 0.007) was present, however, evidenced by the different order of high-gamma power between regions in Figures 4B and 4D.Prefrontal high-gamma power was consistently high compared with other areas, particularly early in the delay period, in both tasks but high-gamma power of other areas, such as cingulate cortex, was more pronounced in the shape task, and high-gamma power of parietal cortex was more pronounced in the spatial task.
To confirm that these findings were specific to the nature of the task executed, we also compared high-gamma power between the 3-s version of the spatial task and the shape task.This analysis confirmed that high-gamma power was higher overall in the spatial task (F 1,1856 = 17.74, p = 2.65E-5, effect size: h 2 = 0.009 for main effect of task).An interaction between regions and tasks was also evidenced (F 5,1853 = 2.68, p = 0.02, effect size: h 2 = 0.007).

DISCUSSION
Our study revealed patterns of oscillatory brain activity during the execution of visual working memory tasks including widespread and regionspecific patterns of activity visible in the LFP.Firstly, we found that the task produced a broadband LFP signal in a brain-wide network, including in areas not traditionally thought to be engaged in visual processing, such as the mesial temporal and cingulate cortex.Secondly, we found that high-gamma power (100-150 Hz), which is likely to be associated with neuronal spiking, 25 was indeed most pronounced in the occipital cortex during the visual stimulus presentation, but this activation did not persist in the delay period, in contradiction to theories supporting maintenance of working memory in the sensory cortex.Thirdly, we found that beta power (16-40 Hz) was most characteristic of the delay (working memory maintenance) period, which however had a nonmonotonic modulation; this included a transient trough of power after the stimulus appearance that rebounded later during the delay period, with the prefrontal cortex being most pronounced in this respect.This pattern of beta power was remarkably similar to the one observed in the monkey prefrontal cortex as subjects performed the identical working memory task but not during passive viewing of the same stimuli, prior to training. 9ur results indicate widespread activation of cortex during visual working memory tasks, in partial agreement with prior results from human imaging studies 11,[26][27][28][29][30] and as predicted by modeling studies analyzing monkey results. 31They also suggest, however, that volume conduction signals such as the LFP (and BOLD) undergo nonmonotonic modulation between the stimulus presentation and working memory maintenance interval, making interpretation of such a signal difficult.Finally, some properties of the prefrontal cortex appeared to be unique in the critical interval of working memory maintenance, in agreement with both human 32 and animal studies. 33These results are also consistent with hierarchical processing of visual information and support the idea that memory may travel along the sensory processing stream of the utilized sensory modality. 34ur task design made it possible to directly compare our findings with neurophysiological results obtained in non-human primate studies, which have the ability to record from large numbers of neurons in very localized areas. 35Our findings were also directly related to imaging studies, which have simultaneous access to all brain regions, but with lower temporal and spatial resolution. 32Our approach therefore offers a path to directly bridge these literatures.

Regional localization of working memory
The locus of working memory maintenance in the brain has been a matter of debate in recent years.Neurons in the prefrontal cortex and areas connected with it generate persistent discharges tuned for stimulus properties during the delay intervals of working memory tasks, in animal 36 and human intracranial recordings. 19Computational models typically simulate persistent activity in neural networks with recurrent connections between units with similar tuning for stimuli, 37 which capture working memory behavior very well, particularly in spatial working memory tasks. 38Based on these results, it has been postulated that the prefrontal cortex plays the primary role in the maintenance of working memory by virtue of generation of persistent spiking activity. 17owever, this idea has been challenged.9][30] On these grounds, it has been suggested that the prefrontal cortex may play a supervisory or control role in working memory, ''highlighting'' the locations of stimuli held in memory, whereas the contents of working memory are maintained in sensory cortex. 16his is not to say, however, that models of prefrontal persistent activity are inconsistent with our findings.It is understood that a distributed network of cortical and subcortical areas generates persistent activity during working memory. 10,40The prefrontal cortex is essential for the ability of the network to maintain persistent discharges, by virtue of the biophysical properties of its neurons and pattern of connectivity. 12,31In our results, high-gamma power was consistently elevated in the prefrontal cortex during the delay period across tasks (Figures 4B and 4D), although this difference was quantitative rather than qualitative in comparison with other areas, and high-gamma power may be an imprecise index of working memory (as discussed in the next section).The presence of oscillatory processes in other brain areas was also revealing.Mesial temporal structures, such as the hippocampus and amygdala, play well-understood roles in long-term memory. 41,42More recent studies, however, suggest engagement during working memory processes, as well. 19,21,43Our results confirmed these findings and suggested modulation of oscillatory processes by the working memory tasks.

Basis of working memory in neural activity
As discussed, models of working memory informed mostly by animal studies have identified persistent discharges generated in the prefrontal cortex and other areas as the critical neural correlate of working memory. 17Such persistent spiking generation is most often associated with gamma frequency oscillations in the LFP. 44Some recent working memory models have emphasized the rhythmicity of spiking discharges themselves and posited that bursting in the gamma frequency range is the critical variable that tracks stimulus information maintenance in working memory. 45,46Human intracranial recordings, too, reveal rhythmicity in the gamma band during working memory tasks. 20,47,48Critical task parameters, such as working memory load, have been shown to modulate neural oscillations. 49,50For this reason, gamma power is considered a marker of task-related activation. 51owever, gamma frequency oscillation in the LFP is at best an imprecise index of neural activity mediating working memory.The LFP represents summation of ionic currents in a cortical volume, in the order of 0.1-0.2mm and are driven by both spiking and synaptic events, e.g., postsynaptic potentials propagated from distant areas that fail to generate action potentials in the area where the recording takes place. 52,53uring presentation of stimuli, correlated bottom-up inputs can serve to synchronize population neuronal spiking, and phases of synchronized excitation by pyramidal neurons followed by inhibition by interneurons can thus produce rhythmicity specifically in the gamma frequency range. 54Less precisely timed or correlated inputs may fail to generate gamma oscillations, and indeed recent animal studies have suggested more prominent changes in the beta rather than gamma frequency range after learning to perform working memory tasks. 8,9Similarly, a recent human study of activation patterns in auditory working memory with intracranial recordings demonstrated that frontal and temporal regions with high decoding accuracy were not accompanied by significant increases in gamma power. 557][58] Beta oscillations are readily detectible in other extracellular field recordings (such as EEG or MEG) and are also a reliable marker of underlying cognitive processes impacting neural circuit interactions, just as gamma oscillations are, 50,59 including working memory and top-down control. 60,61Consistent with the aforementioned animal studies, 8,9 in our study, decrement of beta oscillations was detected during the task execution, and differed systematically between areas, at least around the time of stimulus presentations and early in the delay period of the task.

Limitations of the study
Some limitations apply to our study.First, the number of subjects was relatively small, as was the number of trials they completed.The limited number of subjects affected sampling of some areas disproportionately and particularly the occipital cortex.The position of electrodes in intracranial recordings is dictated by clinical need, and recordings from visual cortex (and other sensory fields) are rare.Our results, from the occipital cortex in particular, ought to be interpreted with caution.
Although our analysis focused on trials completed correctly, it is important to note that epilepsy patients are known to suffer from cognitive deficiencies, including in frontal lobe function and working memory. 62In this respect, patterns of brain activity we describe here may deviate systematically from those of healthy participants.Some patients achieved low performance in the task (for example, patient 4 in Table 1), although many of the errors were due to accuracy and timing of responses rather than failure of working memory per se, and for this reason we opted not to exclude the (correctly completed) trials of any patient from our analysis.
Additionally, our results relied entirely on LFPs.Although providing an informative reflection of neural activity, LFP power does not map strictly onto spiking activity. 53Results from combined methodologies, including neuron recordings from large populations of isolated neurons in humans and animal models, and combined single-neuron and LFP analysis in the near future are making it possible to study in detail the role of areas and patterns of neuronal activity in working memory.

STAR+METHODS
Detailed methods are provided in the online version of this paper and include the following: interval.We constructed time-resolved plots (spectrograms) by dividing the power of the signal by the mean inter-trial interval power at each frequency (which is equivalent to subtracting the baseline power in logarithmic, dB, scale).We then standardized the algorithmic power on the temporal profile at each frequency.

QUANTIFICATION AND STATISTICAL ANALYSIS
Statistical testing of differences between conditions was performed in the following fashion, using only trials that participants completed correctly.First, we calculated power across an entire task epoch: e.g., cue presentation or delay period.Secondly, we averaged power values in these epochs from all available trials of every electrode site, essentially treating each electrode contact as one observation.We then constructed a 1-way or 2-way mixed-effects linear model with fixed-effects terms representing the region, and task and random effects term for each participant as follows: In every case, the analysis was performed for the beta and high-gamma frequency band, defined as 16-40 Hz and 100-150 Hz, respectively, based on prior studies of working memory. 8,20,46These models were implemented in the R computational environment using the lmer R package and Rstudio.F-statistics and p-values were calculated with Satterthwaite's or Kenward-Roger's method for degrees-of-freedom determination.F-statistics were calculated based on the glme model (ImerTest R package).The effect size was determined by the partial eta-squared (h 2 ).Post-hoc pairwise comparisons on any significant main effects were performed with Tukey's method.

Figure 1 .
Figure1.Behavioral tasks and recording methods (A) Spatial manual delayed response task.At the start of each trial, a circle appears in the center of the tablet screen, and the subject moves the stylus into the circle to initiate the trial.After 1 s, a second white dot appears (Cue) at a peripheral location for 0.5 s, after which only the center circle remains.After a delay period, the center circle disappears, and the subject needs to drag the stylus across the screen into the remembered location of the cue.(B) Shape delayed match-nonmatch task.At the start of each trial, a white circle appears in the center of the tablet screen, and the subject moves the stylus into the circle to initiate the trial.After a delay period, a white polygon replaces the center circle for 0.5 s (Cue), followed by the reappearance of the center circle.After a delay, a second convex polygon replaces the center circle for 0.5 s, followed by the reappearance of the center circle.After a second delay, the center circle disappears, and the subject needs to drag the stylus to either a green or red peripheral circle to indicate whether the two polygons were the same or not.(C) Example MRI scan of one patient, with electrode position, based on CT scan, superimposed, where LFP recording were made.

Figure 4 .
Figure 4. Time course of beta and high-gamma power (A) Time resolved induced LFP power in the beta frequency range (16-40 Hz) for the 6-s spatial working memory task, in each of the six brain regions identified.Data are represented as mean (solid line) and standard error of the mean (shaded area).(B) LFP power in the high-gamma range (100-150 Hz).(C) Similarly, time resolved induced LFP power in the beta frequency range (16-40 Hz) for the shape working memory task, in each of the six brain regions identified.(D) LFP power in the high-gamma range (100-150 Hz).

Figure 5 .
Figure 5. High-gamma power for different delay durations Time resolved induced LFP power in the high-gamma range (100-150 Hz) for the two versions of the spatial working memory task, involving 3-s and 6-s delay periods.(A) Mesial temporal regions.(B) Cingulate regions.(C) Temporal regions.(D) Occipital regions.(E) Parietal regions.(F) Prefrontal regions.

Table 1 .
Patient demographic characteristics

TABLE
d RESOURCE AVAILABILITY B Lead contact B Materials availability B Data and code availability d EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS d METHOD DETAILS B Behavioral tasks B Electrode localization B LFP recording, preprocessing and signal analysis d QUANTIFICATION AND STATISTICAL ANALYSIS